About Me

Park Minhoi

I am a Ph.D. candidate in the Department of Urban Big Data Convergence at the University of Seoul. I am also working as a researcher at the Data Science Research Institute at Yonsei University. My research interests include robust machine learning, digital forensics, and multimodal AI.

My Career

Ph.D. candidate in Engineering @ University of Seoul

Department of Urban Big Data Convergence

Sep. 2025 - Present
Ph.D. Student

Researcher @ Yonsei University

From April 2023 to present

Apr. 2023 - Present
Machine Learning and Artificial Intelligence Lab

M.S. in Engineering @ University of Seoul

Department of Urban Big Data Convergence. Graduated.

Mar. 2023 - Aug. 2025
Master of Engineering

Researcher @ University of Seoul

From September 2021 to February 2023

Sep. 2021 - Feb. 2023
Machine Learning and Artificial Intelligence Lab

My Projects

Cyber Crime Investigation Clue Integrated Analysis and Reasoning

Development of integrated analysis and reasoning system for cyber crime investigation clues

Event-based and Syndrome Surveillance Pilot Operation Research

Research on event-based and syndrome surveillance pilot operation systems

Education Content Analysis and Relation Extraction

Development of an Artificial Intelligence Model that Comprehensively Considers Multimodal Elements of Educational Content (Images, Text, Equations, etc.) and Inference of Their Relationships

Education Contents Relationship Analysis with Multimodal Learning

Development of a Multimodal Algorithm for Educational Content Recommendation

Explainable AI for Blood Pressure Estimation

Development and Visualization of Time Series Transformer for PPG-Based Blood Pressure Estimation

Financial and Telecommunication Data Analysis

Development of algorithms for effective analysis and visualization of various structured data, and establishment of strategies for their application in actual police investigations and crime rate prediction

Explainable Graph Neural Network and Molecular Structure

Development of Explainable Graph Node Classification Algorithm

Trustworthy AI Guidebook for Engineer

Derivation of Verification Items and Methods for Trustworthy Artificial Intelligence


My Publications

2025

Peer Reviewed

  • Exploring the Potential of Foundation Models as Reliable AI Contact Centers

    Hoyoon Byun, Minhoi Park, Seolah Kim, Eunbi Kim, and Kyungwoo Song
    Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025)
  • Robust Optimization for PPG-based Blood Pressure Estimation

    Sungjun Lim, Taehwan Kim, Hyeonjeong Lee, Yongha Kim, Minhoi Park, Ki Young Kim, Minho Kim, Ki Hyun Kim, Jinseok Jung, et al.
    Biomedical Signal Processing and Control 105, 107585 (SCIE)
  • RAILL: Retrieval-Augmented Instruction Tuning for Low-Resource Language Model Training

    Yohan Choi, Sungjun Lim, Minhoi Park, Jinseok Jung, Tae-Kyun Kim, Eunbi Kim, Changsu Kim, Kanghee Lee, Hyesu Choi, et al.
    2025 IEEE International Conference on Big Data (BigData), 2124-2129
  • An Intelligent Data Agent for Autonomous Processing of Multimodal Digital Forensic Evidence: Design and Implementation

    Minhoi Park, Juyoung Kang, Hyesu Choi, and Kyungwoo Song
    Journal of Data Forensics Research, 71-93

2024

Peer Reviewed

  • Dirichlet Stochastic Weights Averaging for Graph Neural Networks

    Minhoi Park, Rakwoo Chang, and Kyungwoo Song
    Applied Intelligence 2024. (SCIE, JCR 2023 IF=3.4)
  • Language Model-guided Student Performance Prediction with Multimodal Auxiliary Information

    Changdae Oh, Minhoi Park, Sungjun Lim, and Kyungwoo Song
    Expert Systems With Applications 2024. (SCIE, JCR 2023 IF=7.8)
  • Development of a Multimodal System for Classifying and Automatically Reporting Illegal Online Prostitution Promotional Content Using Text and Image Data

    Minhoi Park, Soyeon Park, Seonghun Yun, Hyesu Choi, Juyoung Kim, and Kyungwoo Song
    Journal of Data Forensics Research 1 (1), 29-46

© Machine Learning and Artificial Intelligence Lab @ Yonsei University